The impact of training schedules on the sleep and fatigue of elite athletes

Effects of total sleep deprivation on endurance cycling performance and heart rate indices used for monitoring athlete readiness

This study investigated effects of total sleep deprivation on self-paced endurance performance, and heart rate (HR) indices of athletes' "readiness to perform". Endurance athletes (n = 13) completed a crossover experiment comprising a normal sleep (NS) and sleep deprivation (SD) condition. Each required completion of an endurance time-trial (TT) on consecutive days (D1, D2) separated by normal sleep or total sleep deprivation. Finishing time, perceived exertion (RPE), mood, psychomotor vigilance (PVT), and HR responses were assessed. Time on D2 of SD was 10% slower than D2 of NS (64 ± 7 vs 59 ± 4 min, P < 0.01), and 11% slower than D1 of SD (58 ± 5 min, P < 0.01). Subjective to objective (RPE:mean HR) intensity ratio was higher on D2 of SD compared with D2 of NS and D1 of SD (P < 0.01). Mood disturbance and PVT mean response time increased on D2 of SD compared with D2 of NS and D1 of SD. Anaerobic threshold and change in TT time were correlated (R = -0.73, P < 0.01). Sleep helps to optimise endurance performance. Subjective to objective intensity ratios appear sensitive to effects of sleep on athletes' readiness. Research examining more subtle sleep manipulation is required.

Relationships Between Sport Specialization, Sleep, and Subjective Well-Being in Female Adolescent Athletes

OBJECTIVE

To evaluate the relationship between sport specialization, sleep, and subjective well-being in female youth soccer players.

DESIGN

Prospective cohort study.

SETTING

Community soccer organization.

METHODS

During a 4-month season, 52 female youth soccer players (aged 13-18 years) reported daily training load (TL) and every morning recorded sleep duration and stress, mood, fatigue, soreness, and sleep quality from -3 (worst) to +3 (best). As all the athletes participate in soccer as their primary sport for over 8 months of the year, players were considered specialized if they participated in soccer exclusively and had previously quit another sport to focus on soccer. Least-square mean values from linear mixed effects models were used to compare TL, subjective well-being, and sleep while adjusting for individual repeated measures.

RESULTS

Daily TL during the season did not differ between specialized and nonspecialized athletes (412 ± 24 vs 415 ± 19 arbitrary units, P = 0.96, respectively). Despite similar nightly sleep duration (8.10 ± 0.14 vs 8.25 ± 0.11 hours, P = 0.42), specialized athletes were found to have lower (worse) fatigue (1.02 ± 0.14 vs 1.50 ± 0.11, P = 0.010), soreness (0.66 ± 0.18 vs 1.23 ± 0.14, P = 0.013), mood (1.32 ± 0.12 vs 1.72 ± 0.10, P = 0.013), and sleep quality (1.07 ± 0.13 vs 1.42 ± 0.10, P = 0.035) than the nonspecialized group. Although stress was lower (worse) among the specialized athletes, the difference was not statistically significant (0.97 ± 0.16 vs 1.32 ± 0.13, P = 0.092).

CONCLUSIONS

Among female youth soccer players, sport specialization was associated with impairments in subjective well-being and sleep quality. Additional research is necessary to determine whether this relationship is causal or if factors that influence sport specialization also influence sleep and subjective well-being.

Sleep quality associated with mood in elite athletes

Objectives: This study aimed to analyze the association between sleep quality and mood in elite athletes of different competitive levels. Methods: Participants were 1041 elite athletes (aged 20.82 ± 6.62 years), with 671 men (64.5%/21.52 ± 6.90 years) and 370 women (35.5%/19.55 ± 5.89 years) from 10 individual sports and 6 team sports. Participants self-reported sleep quality on a Likert-type scale and mood was measured with the Brunel Mood Scale (BRUMS). The data were analyzed using the Kruskal-Wallis test, and binary logistic regression. Results: Results revealed that athletes who compete internationally are 84% more likely to have poor sleep quality than athletes who compete at a regional level. International athletes with good sleep quality showed greater vigor. National athletes with poor sleep quality showed more confusion, depression, and fatigue. Thus, mood and competitive level are factors associated with sleep quality. Confusion, fatigue, and tension impair sleep, and vigor reduces the likelihood of poor sleep. Conclusions: Sleep should be monitored, especially in international level athletes, in order to prevent sleep disorders during competitions. Coaches and athletes should use techniques and strategies for appropriate management of sleep and mood, to maintain the athletes in optimal condition before important competitions.

Sleep Profiles of Elite Swimmers During Different Training Phases

Walsh, JA, Sanders, D, Hamilton, DL, and Walshe, I. Sleep profiles of elite swimmers during different training phases. J Strength Cond Res 33(3): 811-818, 2019-This study aims to describe the sleeping patterns during different training phases in competitive swimmers. Twelve national- and international-level swimmers (3 females and 9 males) were monitored during 4 different phases, consisting of a preparation training phase, a taper phase, a competition phase, and a rest phase. Sleep parameters were assessed using wrist activity monitors and self-reported sleep diaries. There was a moderately higher (d = 0.70-1.00) sleep onset latency during the competition phase compared with taper, train, and rest phases. Trivial to small differences were observed for total sleep time between phases (d = 0.05-0.40). Sleep efficiency was moderately higher (d = 0.60-0.75) in the training and taper phases compared with competition and rest. Restfulness and fragmentation index (FI) were lowest in the rest with differences between phases being small (d = 0.43-0.51) for restfulness and small to moderate (d = 0.43-0.62) for FI. Time in and out of bed was very largely later (d = 1.96-2.34) in rest compared with the other phases. Total nap time was moderately lower in rest (d = 1.13-1.18) compared with the training and competition phases, whereas there was a small difference (d = 0.46) compared with taper. To conclude, while there were trivial to small differences in sleep quantity between phases, there are small to moderate differences in other sleep parameters. Specifically, sleep onset latency was higher during the competition phase. In addition, this study highlights the substantial between-individual variations in sleep responses during different training phases.

Does Night Training Load Affect Sleep Patterns and Nocturnal Cardiac Autonomic Activity in High-Level Female Soccer Players?

Purpose: To analyze whether exercise training conducted at night disturbs sleep and affects nocturnal cardiac autonomic control in high-level female athletes. Methods: A total of 18 high-level female soccer players (mean [SD] age 20.4 [2.1] y) wore actigraphs and heart-rate (HR) monitors during night sleep throughout night training days (n = 8) and resting days (n = 8), for 3 consecutive weeks. This was a longitudinal study that measured internal training load, sleep, nocturnal cardiac autonomic activity, and well-being ratings prior to training sessions. Results: Training load varied across training days (eg, training impulse range, mean [SD]; effect size, ES [95% confidence interval]: 72.9 [18.8] to 138.4 [29.6] a.u.; F_4,62 = 32.331; ηp2=.673 [.001-.16], large effect; P < .001). However, no differences in subjective well-being ratings were observed, although ES was large. Total sleep time (training days vs resting days: 07:17 [00:47] h vs 07:51 [00:42] h; ES = 0.742 [0.59-0.92], P = .005; moderate effect) and sleep-onset time (00:58 [00:19] h vs 00:44 [00:16] h; ES = 0.802 [0.68-0.94], P = .001; moderate effect) were negatively affected after night training. In addition, small effects were detected for wake-up time, time in bed, and sleep latency (P > .05). No differences were detected in HR variability during sleep (range of lnRMSSD: 4.3 [0.4] to 4.5 [0.4] ln[ms] vs 4.6 [0.3] to 4.5 [0.4] ln[ms]; F_3,52 = 2.148; P > .05; ηp2=.112 [.01-.25], medium effect), but HR during sleep was significantly higher after training days (range of HR: 56 [4] to 63 [7] beats/min vs 54 [4] to 57 [6] beats/min; F_2,32 = 15.956; P < .001; ηp2=.484 [.20-.63], large effect). Conclusion: Overall, the results indicate that exercise training conducted at night may disturb sleep and affect HR, whereas limited effects can be expected in HR variability assessed during sleep in high-level female soccer players.

Daytime naps can be used to supplement night-time sleep in athletes

This study examined the efficacy of daytime napping to supplement night-time sleep in athletes. Twelve well-trained male soccer players completed three conditions in a randomised, counterbalanced order: 9 h in bed overnight with no daytime nap (9 h + 0 h); 8 h in bed overnight with a 1-h daytime nap (8 h + 1 h); and 7 h in bed overnight with a 2-h daytime nap (7 h + 2 h). Sleep was assessed using polysomnography. The total amount of sleep obtained in the three conditions was similar, i.e. 8.1 h (9 h + 0 h), 8.2 h (8 h + 1 h), and 8.0 h (7 h + 2 h). Daytime napping may be an effective strategy to supplement athletes' night-time sleep.

Observing Ramadan and sleep-wake patterns in athletes: a systematic review, meta-analysis and meta-regression

Objective

To evaluate the effect of observing Ramadan on athletes’ sleep patterns.

Design

Systematic review and meta-analysis.

Data sources

The entire content of PubMed/MEDLINE and Web of Science.

Eligibility criteria for selecting studies

Single-group, prepost and cross-over design studies conducted in athletes aged ≥18 years, training at least twice a week and published in English before 12 July 2018 were included. Studies assessing sleep quantity, quality, daytime sleepiness and/or daily naps based on objective or subjective methods were deemed eligible.

Study appraisal

The methodological quality was assessed using ‘QualSyst’.

Results

Of 13 selected articles, 7 were of strong quality, 3 were moderate and 3 were weak. 11 studies evaluated total sleep time (TST); this decreased during Ramadan in 4 studies, increased in 1 and remained unchanged in 6. Pooled TST findings indicated a moderate effect size (− 0.97, SE=0.37, 95% CI −1.69 to −0.25, t=−2.64, p=0.01) with significant heterogeneity but no publication bias. Meta-regressions showed no effects of study year, age, sample size, type of sport or competition level, but there were effects of country (with France and Tunisia being the most affected countries and Turkey the least affected, Q=32.14, p<0.0001) and study design (Q=7.74, p=0.02). Four studies measured self-reported sleep quality and it decreased in three studies. One study of sleep architecture reported more frequent waking and more light sleep during Ramadan. Daily nap duration was increased in two studies, but daytime sleepiness remained unchanged in four studies.

Conclusion

When athletes continue to train at least two times/week while observing Ramadan, TST is decreased compared with athletes’ baseline levels.

Effects of morning vs. evening combined strength and endurance training on physical performance, sleep and well-being

The aim of the present study was to examine how combined strength and endurance training in the morning and evening influences the adaptations in strength and endurance performance, perception of time management, psychological well-being and sleep. The combined training period lasted for 24 weeks and the participants were divided into the morning training (MG, n = 18), evening training (EG, n = 24) and control groups (CG, n = 10). Isometric leg press force (iLP), maximal oxygen consumption (VO₂max), sleep behavior, fatigue, time management, motivation, self-esteem and health-related quality of life (HRQoL) were assessed. Morning to evening difference in iLP was observed in both MG and EG at Pre and Post, with higher force values in the evening, but not for VO₂max. iLP force increased significantly in EG in the morning (p < 0.001) and evening (p = 0.010). VO₂max increased in MG and EG both in the morning (both p < 0.001) and in the evening (MG: p < 0.001; EG: p = 0.003). Participants of the present study slept 7-8 h per night and the self-reported sleep duration, get-up time and the average time to go to bed were similar between the groups and did not change from Pre to Post. From HRQoL dimensions, the score for bodily pain decreased in MG (p = 0.029) and significant between-group differences were observed for Pre-Post changes in MG and EG (p = 0.001) as well as between MG and CG (p < 0.001). In vitality, a significant between-group difference was observed for Pre to Post changes in MG and EG (p = 0.014). Perception of time management decreased in EG (p = 0.042) but stayed unchanged for MG and CG. For the intrinsic motivation to participate, significant between-group differences were observed for MG and EG (p = 0.033) and between MG and CG (p = 0.032) for Pre to Post changes. Self-esteem improved in MG (p = 0.029) and EG (p = 0.024). The present combined strength and endurance training program performed in the morning and in the evening led to similar improvements in strength and endurance performance. Training in the morning or in the evening did not disrupt the already good sleep behavior and it was able to further increase the self-esteem. Although training in the morning hours may leave more time for free time activities or social life (i.e. family and friends) compared to the evening training, it might be more challenging to stay motivated to participate in prolonged training programs in the morning hours.

Nocturnal Activity Is Not Affected by a Long-Duration, Low-Intensity Single Exercise Bout

The aim of the current study was to examine whether prolonged low-intensity aerobic exercise could affect nocturnal activity in healthy individuals. Twenty-one healthy adults (24 ± 3.7 years; 9 females) were enrolled in this study. All participants participated in a 3-h low-intensity walking exercise protocol. Standard biochemical indices were assessed before the exercise protocol and at 72 h. Nocturnal activity and various indices of health were recorded for five consecutive days. The score of muscle pain peaked the night after the exercise protocol (p < 0.05) and returned to baseline two days after. No statistical differences were found in any of the parameters examined, including nocturnal activity. Prolonged low-intensity exercise does not affect nocturnal activity. The anecdotal reports suggesting that exercise or/and physical activity could worsen symptoms of motor restlessness during sleep in sleep disorders, such as restless legs syndrome and periodic limb movements, are not supported by this study. However, these findings need to be verified in clinical populations, as well as by using protocols with different forms of exercise.

Athletes' rest-activity circadian rhythm differs in accordance with the sport discipline

The correct expression of circadian rhythmicity is crucial for the body homeostasis. The rest-activity circadian rhythms (RARs) are involved in the control of the sleep-wake cycle and altered RARs could lead to a compromised health status. Many studies focused on examining sleep behavior and circadian rhythms in physically active subjects or athletes but, unexpectedly, no data on RARs are available. Therefore, we studied the existence of the RAR in athletes and the possible difference in RAR's characteristics among sport disciplines. The study had a prospective observational design and RARs were recorded for five consecutive training days through actigraphy (Actiwatch 2 actigraph; Philips Respironics, OR, USA) in 43 athletes (mean age: 25.6 ± 3.2 years). Athletes competed in three different disciplines and had different training schedules and competition levels: professional triathletes (N = 10; 6 females and 4 males) had 2 morning (08:30-12:00) and 1 afternoon (15:00-17:00) training sessions, professional volleyball players (N = 19; 12 females and 7 males) used to train once in the morning (09:00-11:30) and once in the afternoon (15:00-18:00), and non-professional soccer players (N = 14; all males) trained always late in the evening (20:30-22:30). To determine the existence of RARs, the activity counts (A.C.) data were analyzed using the single and the population mean cosinor method; a one-way analysis of variance (ANOVA) followed by the Tukey-Kramer post-hoc test was used for the comparison of RAR characteristics among soccer, volleyball and triathlon athletes. Partial eta squared (ή_p²) was used to determine the magnitude of the effect for significant outcomes (α = 0.05) in ANOVA. The presence of a significant RAR both for each of the 43 athletes (p < 0.001) and for the three categories of athletes (p < 0.001) was observed. RARs differed among sport disciplines: the Midline Estimating Statistic of Rhythm (MESOR) was significantly higher in triathletes (mean: 347 A.C. with 95% Confidence Interval [CI]: 314-379) compared to both volleyball (mean: 188 A.C. with 95% CI: 173-203; p < 0.001) and soccer players (mean: 289 A.C. with 95% CI: 267-312; p < 0.01) with ή_p² = 0.72. Amplitude (A) values showed the same significant trend of MESOR data (ANOVA: p < 0.001; ή_p² = 0.65) while the acrophase (Φ) occurred at 18:28 for soccer players, significantly later than triathlon (15:20 h; p < 0.001) and volleyball players (16:24 h; p < 0.001) (ANOVA: p < 0.001; ήp2 = 0.84). The higher training duration and intensity reached by triathlon athletes in the morning sessions caused a phase advance of their RAR's acrophase Φ and higher MESOR and A amplitude compared to volleyball players and triathletes. Therefore, different sport disciplines require different training schedules, training loads and intensities that translate into different RARs. Strength coaches and medical staff of professional teams should strongly consider actigraphy as a practical and powerful tool to monitor RARs, sleep behavior, and the activity levels of their athletes; highlighting potential circadian disruptions through actigraphy could be helpful to prevent musculoskeletal injuries.

Physiological and pathological covariates of persistent concussion-related fatigue: results from two regression methodologies

BACKGROUND

Fatigue severity in persons with mild traumatic brain injury (mTBI) has received little research attention, despite its typically positively skewed nature. Investigation of covariates across a range of fatigue severity may provide insight into important contributors.

OBJECTIVE

To assess the relative significance of a priori-hypothesized covariates of physiological and pathological (mental and physical) fatigue in persons with mTBI/concussion, applying ordinary least squares (OLS) and quantile regression (QR) approaches.

METHODS

We conducted a cross-sectional investigation in 80 participants with mTBI/concussion (mean age 45.4 ± 10.1 years, 59% male). The fatigue severity scale (FSS) was used as an outcome measure. Predictors of this outcome, grouped into physiological and pathological models of fatigue were assessed using OLS and QR.

RESULTS

The mean total FSS score was 46.13 ± 14.59, and the median was 49 (interquartile range 37-57), demonstrating positive skewness. Fatigue severity was associated with variables within the mental, psychological and psychiatric domains at different levels of the fatigue score distribution.

CONCLUSION

Results highlighted that some covariates had a significant impact on the FSS total score at non-central parts of its distribution, while others exhibited significant impact across the entire distribution. Addressing covariates of fatigue across the severity continuum can enhance research and clinical management.

Influence of Self-reported Fatigue and Sex on Baseline Concussion Assessment Scores

Background:

Baseline concussion assessments are advocated to provide an objective preinjury point of comparison for determining the extent of postconcussion neurological deficits and to assist with return-to-activity decision making. Many factors, including testing environment, proctor availability, and testing group size, can influence test accuracy and validity; however, it is unknown how self-reported fatigue affects test scores.

Purpose:

To investigate the influence of self-reported fatigue and patient sex on baseline concussion assessment scores.

Study Design:

Cross-sectional study; Level of evidence, 3.

Methods:

Participants included 494 healthy Division I college student-athletes (221 women, 273 men; mean ± SD age, 20.0 ± 1.3 years). During preseason baseline testing, participants were asked to rate their fatigue on a scale from 0 to 100 based on how they normally feel and function each day (0, completely exhausted; 100, completely awake and alert). Each participant then completed a multimodal baseline concussion assessment, including a graded symptom checklist (number of symptoms endorsed and total symptom severity score), Standardized Assessment of Concussion (SAC), Balance Error Scoring System (BESS), and CNS Vital Signs computerized neurocognitive testing. Multiple linear regressions tested whether self-reported fatigue and sex predicted baseline concussion examination scores.

Results:

Athletes with higher self-reported fatigue levels (ß = –0.014, P < .01) and female athletes (ß = –0.216, P < .01) reported more total symptoms. Being male (ß = 0.856, P < .01) increased the likelihood of endorsing zero symptoms versus any symptoms by a factor of 2.40. Women also had significantly higher SAC scores (ß = 0.569, P < .001), BESS scores (ß = –2.747, P < .001), and CNS Vital Signs summary scores (ß = 4.506, P < .001). SAC, BESS, and CNS Vital Signs scores were not predicted by fatigue level (P > .05).

Conclusion:

Female athletes and fatigued athletes endorsed more symptoms and higher symptom severity at baseline. Using total symptom endorsement and total symptom severity scores as part of the postinjury management is a common practice. The current data suggest that levels of reported exhaustion can influence concussion assessment scores meant to represent a healthy baseline and likely would interfere with postinjury assessment scores.

Effects of a Short Daytime Nap on Shooting and Sprint Performance in High-Level Adolescent Athletes

PURPOSE

To investigate the sport-specific performance effect of a brief afternoon nap on high-level Asian adolescent student-athletes who were habitually short sleepers.

METHODS

Participants were randomly assigned to a nap or nonnap (reading) condition. In the first study, 12 male shooters (13.8 [1.0] y) performed a shooting assessment (20 competition shots) with heart-rate variability monitored during the assessment. In the second study, 19 male track-and-field athletes (14.8 [1.1] y) performed a 20-m sprint-performance assessment. Subjective measures of sleepiness and alertness were obtained in both studies.

RESULTS

The brief nap had no effect on any measure of shooting performance (P > .05) or autonomic function (P > .05) in shooters. However, the fastest 20-m sprint times increased significantly (P < .05) from 3.385 (0.128) s to 3.411 (0.143) s, with mean 2-m times trending toward significance (P < .1) among the track-and-field athletes. No significant differences were observed in any other measures.

CONCLUSIONS

The results of the research indicate varying effects of naps between sport-specific performance measures. Napping had no effect on shooting performance, whereas a negative effect existed in 20-m sprint performance, potentially due to sleep inertia. Considering these findings, some caution is warranted when advocating naps for adolescent athletes.

Sleep-Related Issues for Recovery and Performance in Athletes

The body of research that reports the relevance of sleep in high-performance sports is growing steadily. While the identification of sleep cycles and diagnosis of sleep disorders are limited to lab-based assessment via polysomnography, the development of activity-based devices estimating sleep patterns provides greater insight into the sleep behavior of athletes in ecological settings. Generally, small sleep quantity and/or poor quality appears to exist in many athletic populations, although this may be related to training and competition context. Typical sleep-affecting factors are the scheduling of training sessions and competitions, as well as impaired sleep onset as a result of increased arousal prior to competition or due to the use of electronic devices before bedtime. Further challenges are travel demands, which may be accompanied by jet-lag symptoms and disruption of sleep habits. Promotion of sleep may be approached via behavioral strategies such as sleep hygiene, extending nighttime sleep, or daytime napping. Pharmacological interventions should be limited to clinically induced treatments, as evidence among healthy and athletic populations is lacking. To optimize and manage sleep in athletes, it is recommended to implement routine sleep monitoring on an individual basis.

Sleep Data, Physical Performance, and Injuries in Preparation for Professional Mixed Martial Arts

The purpose of this investigation is to present observational data regarding sleep variables in professional Mixed Martial Arts (MMA) athletes. These sleep performance measures were related to physical performance and injury in MMA athletes. Eight professional athletes were placed into a quasi-controlled, multivariable fight-camp environment for a six-week period in preparation for fight competition. Throughout a six-week fight camp environment, athletes were continuously monitored for sleep performance measures (sleep latency, sleep efficiency, onset, and wake variances) via validated wearable sleep monitoring technology. Athletes were tested seven days prior to competition on measures of physical performance (vertical jump, VO₂max, heart rate recovery, prowler sled push, and pull-ups). Multiple correlational analyses were utilized to assess relationships between all sleep and physical performance measures. There were significant (P < 0.05) correlations between sleep latency and VO₂max, heart rate recovery, prowler sled push, vertical jump, and missed practice sessions. There were also significant (P < 0.05) correlations between average fall asleep time and heart rate recovery. Lastly, there were significant (P < 0.05) correlations between sleep efficiency, heart rate recovery, and missed practice sessions. MMA athletes who exhibited consistency in sleep demonstrated stronger relationships with performance testing during the fight-camp period.

Travel fatigue and sleep/wake behaviors of professional soccer players during international competition

OBJECTIVE

The magnitude of travel completed by professional Australian soccer teams during domestic competition is substantial. The inclusion of Australian soccer teams into the Asian Champions league has seen additional stress placed on soccer players' training and competition schedules. For management staff, the complexity of organizing training and travel schedules during domestic competition and the Asian Champions league is challenging.

DESIGN

Case study.

PARTICIPANTS

Seven male professional soccer players (mean ± SD: age 25.2 ± 3.2 years, height 182.8 ± 5.2 cm, body mass 84.6 ± 7.4 kg).

MEASUREMENTS

This study examined the sleep and fatigue levels of Australian soccer players during an intensive home and away travel schedule during the Asian Champions league. Seven male professional soccer players' (mean ± SD: age 25.2 ± 3.2 years, height 182.8 ± 5.2 cm, body mass 84.6 ± 7.4 kg) sleep/wake behavior was assessed using sleep diaries and wrist activity monitors for 19 days, including 9 days before, 5 days during, and 4 days after a home and away group stage match of the Asian Champions league. Analyses examined differences in sleep/wake behavior and fatigue levels between day type (training day, rest day, pregame, and postgame) and between sleep location (Adelaide, during flight, and Hiroshima).

RESULTS

Sleep/wake behavior and fatigue levels were poorest the night immediately after games compared to the night before games, training days, and rest days. Soccer players' sleep/wake behaviors were disrupted during flights such that they obtained 3.6 hours less sleep during flights compared to sleep in Adelaide (7.0 ± 1.6 hours) and Hiroshima (7.0 ± 2.1 hours).

CONCLUSION

The sleep/wake behaviors of professional soccer players are compromised when they are required to travel and compete in multiple matches within a short period of time.

Evening electronic device use and sleep patterns in athletes

The present study aimed to investigate pre-sleep behaviours (including evening electronic device use) and sleep quantity in well-trained athletes. Seventy well-trained athletes (44 females, 26 males) aged 21 ± 4 y from a range of team and individual sports were asked to complete an online sleep diary for 7 days. The sleep diary included questions about pre-sleep behaviours (e.g. napping, caffeine intake), electronic device use in the 2 h prior to bedtime (e.g. type of device and duration of use) and sleep (e.g. time in bed, sleep onset latency). On average, athletes spent 8:20 ± 1:21 h in bed each night. Associations between age, time in bed and sleepiness suggested that younger athletes spent more time in bed (B = -0.05, p = 0.001) but felt sleepier (r = -0.32, p < 0.01) than older athletes. On average, athletes mostly used electronic devices for 0-30 min prior to sleep. The use of multiple devices in the evening was associated with more perceived difficulty in falling asleep (B = 0.22, p = 0.03), but no associations existed with other sleep variables. In summary, younger athletes may require later start times or improved sleep quality to resolve excessive sleepiness.

Sleep environments and sleep physiology: A review

Sleep loss impairs task performance and post-physical activity recovery, cognitive performance and mood, heightens fatigue and decreases vigour; poor sleep quality impairs decision-making, the speed and accuracy of task performance, and post-exercise recovery. Sleep time and quality are affected by age, psychological and physiological conditions, culture and environmental factors. Skin temperature, rapid temperature change and sweating during sleep can significantly reduce sleep quality. Hence, the thermal properties of bedding and sleepwear, both in steady-state and transient ambient temperature conditions, are logically important factors. Research to date on sleeping thermal microclimates and their effect on sleep quality is scarce. This present review covers the fundamental elements of human sleep, highlighting physically active people, such as athletes, and the influence of sleepwear and bedding on sleep thermal microclimates, as well as the research methods that have been and could be used in this field. This review identifies opportunity for future research direction and approaches to understanding thermal environments that may support better human sleep.

Effects of training and competition on the sleep of elite athletes: a systematic review and meta-analysis

Objectives

To characterise the sleep of elite athletes and to identify factors associated with training and competition that negatively affect sleep.

Design

Prognosis systematic review.

Data sources

Three databases (PubMed, SCOPUS and SPORTDiscus) were searched from inception to 26 February 2018.

Eligibility criteria for selecting studies

Included studies objectively reported total sleep time (TST) and/or sleep efficiency (SE) in elite athletes. Studies were required to be observational or to include an observational trial.

Results

Fifty-four studies were included. During training, many studies reported athletes were unable to achieve TST (n=23/41) and/or SE (n=16/37) recommendations. On the night of competition, most studies reported athletes were unable to achieve TST (n=14/18) and/or SE (n=10/16) recommendations. TST was shorter (60 min) the night of competition compared with previous nights. SE was lower (1%) the night of competition compared with the previous night. TST was shorter the night of night competition (start ≥18:00; 80 min) and day competition (20 min) compared with the previous night. SE was lower (3%–4%) the night of night competition but unchanged the night of day competition compared with previous nights. Early morning training (start <07:00), increases in training load (>25%), late night/early morning travel departure times, eastward air travel and altitude ascent impaired sleep.

Conclusion

Athletes were often unable to achieve sleep recommendations during training or competition periods. Sleep was impaired the night of competition compared with previous nights. Early morning training, increases in training load, travel departure times, jet lag and altitude can impair athletes’ sleep.

PROSPERO registration number

CRD42017074367.

From pillow to podium: a review on understanding sleep for elite athletes

Sleep is considered vital to human health and well-being, and is critical to physiological and cognitive functioning. Elite athletes experience high training and competition demands, and are often exposed to various factors, situations, and environments that can cause sleep impairments. Previous research has shown that athletes commonly experience sleep loss in the lead up to and following competition, which could have significant impacts on their preparation, performance, and recovery. In particular, the results from previous research show significant reductions in total sleep time (~1:40 h:min) and significant increases in sleep latency (~45 minutes) following evening competition. Napping is common in both the training and competition setting in athletes; however, research on the effect of napping on physiology and performance is limited. In contrast, research on strategies and interventions to improve sleep are increasing in the athletic population, with sleep hygiene research resulting in significant improvements in key sleep indices. This review investigates the physiological importance of sleep in athletes, current tools to monitor athletes' sleep, the role of sleep for cognitive functioning and athletic performance, the prevalence of sleep disturbances and the potential mechanisms causing sleep disturbances, the role of napping, and different intervention strategies to improve sleep.

Relationships Between Training Load, Sleep Duration, and Daily Well-Being and Recovery Measures in Youth Athletes

PURPOSE

To assess the relationships between training load, sleep duration, and 3 daily well-being, recovery, and fatigue measures in youth athletes.

METHODS

Fifty-two youth athletes completed 3 maximal countermovement jumps (CMJs), a daily well-being questionnaire (DWB), the perceived recovery status scale (PRS), and provided details on their previous day's training loads (training) and self-reported sleep duration (sleep) on 4 weekdays over a 7-week period. Partial correlations, linear mixed models, and magnitude-based inferences were used to assess the relationships between the predictor variables (training and sleep) and the dependent variables (CMJ, DWB, and PRS).

RESULTS

There was no relationship between CMJ and training (r = -.09; ±.06) or sleep (r = .01; ±.06). The DWB was correlated with sleep (r = .28; ±.05, small), but not training (r = -.05; ±.06). The PRS was correlated with training (r = -.23; ±.05, small), but not sleep (r = .12; ±.06). The DWB was sensitive to low sleep (d = -0.33; ±0.11) relative to moderate; PRS was sensitive to high (d = -0.36; ±0.11) and low (d = 0.29; ±0.17) training relative to moderate.

CONCLUSIONS

The PRS is a simple tool to monitor the training response, but DWB may provide a greater understanding of the athlete's overall well-being. The CMJ was not associated with the training or sleep response in this population.

Night Games and Sleep: Physiological, Neuroendocrine, and Psychometric Mechanisms

Context: Night games are a regular occurrence for team-sport athletes, yet sleep complaints following night competitions are common. The mechanisms responsible for reported sleep difficulty in athletes are not understood. Methods: An observational crossover design investigating a night netball game and a time-matched rest day in 12 netball athletes was conducted to ascertain differences in physiological (core temperature), psychometric (state and trait), and neuroendocrine (adrenaline, noradrenaline, and cortisol) responses. Results: Following the night game, athletes experienced reduced sleep durations, lower sleep efficiency, early awakenings, and poorer subjective sleep ratings compared with the rest day. No differences were found between core temperature, state psychometric measures, and cortisol at bedtime. Adrenaline and noradrenaline concentrations were elevated compared with the time-matched rest day prior to (26.92 [15.88] vs 12.90 [5.71] and 232.6 [148.1] vs 97.83 [36.43] nmol/L, respectively) and following the night game (18.67 [13.26] vs 11.92 [4.56] and 234.1 [137.2] vs 88.58 [54.08] nmol/L, respectively); however, the concentrations did not correlate to the sleep variables (duration, efficiency, and sleep-onset latency). A correlation (rs = −.611) between sleep efficiency and hyperarousal (trait psychometric measure) was found. Conclusions: Athletes experienced poor sleep following a night game. Furthermore, results suggest that athletes who have a tendency toward a high trait arousal may be more susceptible to sleep complaints following a night game. These data expand knowledge and refute frequently hypothesized explanations for poor sleep following night competition. The results may also help support staff and coaches target strategies for individual athletes at a higher risk of sleep complaints.

The Variability of Sleep Among Elite Athletes

Practicing sport at the highest level is typically accompanied by several stressors and restrictions on personal life. Elite athletes’ lifestyle delivers a significant challenge to sleep, due to both the physiological and psychological demands, and the training and competition schedules. Inter-individual variability of sleep patterns (e.g., sleep requirements, chronotype) may have important implications not only for recovery and training schedules but also for the choice of measures to possibly improve sleep. This article provides a review of the current available literature regarding the variability of sleep among elite athletes and factors possibly responsible for this phenomenon. We also provide methodological approaches to better address the inter-individual variability of sleep in future studies with elite athletes. There is currently little scientific evidence supporting a specific influence of one particular type of sport on sleep; sleep disorders may be, however, more common in strength/power and contact sports. Sleep behavior may notably vary depending on the athlete’s typical daily schedule. The specificity of training and competition schedules possibly accounts for the single most influential factor leading to inconsistency in sleep among elite athletes (e.g., “social jet lag”). Additionally, athletes are affected by extensive exposure to electric light and evening use of electronic media devices. Therefore, the influence of ordinary sleep, poor sleep, and extended sleep as important additional contributors to training load should be studied. Future experimental studies on sleep and elite sport performance should systematically report the seasonal phase. Boarding conditions may provide a good option to standardize as many variables as possible without the inconvenience of laboratory. The use of interdisciplinary mixed-method approaches should be encouraged in future studies on sleep and elite sport. Finally, high inter- and intra-individual variability in the athletes’ sleep characteristics suggests a need for providing individual responses in addition to group means.

Longer Sleep Durations Are Positively Associated With Finishing Place During a National Multiday Netball Competition

Juliff, LE, Halson, SL, Hebert, JJ, Forsyth, PL, and Peiffer, JJ. Longer sleep durations are positively associated with finishing place during a national multiday netball competition. J Strength Cond Res 32(1): 189-194, 2018-Sleep is often regarded as the single best recovery strategy available to an athlete, yet little is known about the quality and quantity of sleep in athletes during multiday competitions. This study objectively evaluated sleep characteristics of athletes during a national netball tournament. Using wrist actigraphy monitors and sleep diaries, 42 netballers from 4 state teams were monitored for the duration of a tournament (6 days) and 12 days before in home environments. Significant differences were found between teams based on final competition standings, suggesting enhanced sleep characteristics in athlete's whose team finished higher in the tournament standings. The top 2 placed teams when compared with the lower 2 placed teams slept longer (8:02 ± 36:43; 7:01 ± 27:33), had greater time in bed (9:03 ± 0:52; 7:59 ± 0:54) and reported enhanced subjective sleep ratings (2.6 ± 0.5; 2.3 ± 0.6). Sleep efficiency was no different between teams. A strong correlation (r = -0.68) was found indicating longer sleep durations during competition were associated with higher final tournament positions. Encouraging athletes to aim for longer sleep durations in competition, where possible, may influence the outcome in tournament style competitions.

Risk factors for precompetitive sleep behavior in elite female athletes

BACKGROUND

Sleep is of major importance for the athletes' short and long-term health, performance and recovery; however, published studies on athletes' sleep and even fewer before competition are scarce. This study evaluated the risk factors of sleep in young female gymnasts before an international competition.

METHODS

Sixty-seven rhythmic gymnasts (M=18.7, SD=2.9 years) of high performance (M=36.6, SD=7.6 h/week) were evaluated regarding training and sport practice, body composition, sleep duration, daytime sleepiness by the Epworth Sleepiness Scale, sleep quality by the Pittsburgh Sleep Quality Index, precompetitive anxiety by the Sport Competition Anxiety Test form A, and detailed dietary intake just prior to a world competition.

RESULTS

The majority of the participants (83.6%) presented reduced body fat levels (M=9.1, SD=2.1%) and low energy availability (EA, M=31.5, SD=11.9 kcal/kgFFM/day). They slept 8h10±1h30/night on weekdays and 8h40±00h40/night on weekends, 67% suffered from mild daytime sleepiness and 78% had a reduced sleep quality. Precompetitive anxiety was on average moderate (M=22.7, SD=3.2). The risk factors for short sleep duration were: 1.92 for a training volume>30 hours/week (95% CI 0.84-4.39), 4.57 for menstruation (95% CI 1.17-17.77), 6.62 for bedtime ≥11:00 PM (95% CI 1.74-25.10), 1.40 for BF<12% (95% CI 1.03-1.92), 2.19 for FFM<30 kg (95% IC 0.94-4.94), 2.37 for BMR<1100 kcal/day (95% CI 1.06-5.32), 1.90 for EEE≥700 kcal (95% CI 0.92-3.93) and 3.17 for EA<45 kcal/kg FFM/day (95% CI 0.84-6.59). Age, performance, sleep duration on weekdays and precompetitive stress were also predictors for a reduced sleep quality and/or abnormal daytime sleepiness.

CONCLUSIONS

Age, training regime, menstruation, individual preferences for bedtime, body composition and energy were important predictors of gymnasts' precompetitive sleep with consequences upon their sleep duration, SQ and DS.

Sleep duration, body composition, dietary profile and eating behaviours among children and adolescents: a comparison between Portuguese acrobatic gymnasts

Sleep, body composition and dietary intake are crucial for athletes' health and performance but have never been investigated in acrobatic gymnasts. Thus, this study aimed to evaluate sleep, body composition, dietary intake and eating behaviours of acrobatic gymnasts. Using a cross-sectional study, 82 Portuguese acrobatic gymnasts (12.8 ± 3.1 years, 61 females and 21 males) were evaluated during the competitive period to collect training data, sleep duration, body composition, dietary intake and eating behaviours before, during and after practices. Most of the gymnasts (91.5%) slept less than 8 h/night. Female adolescents slept significantly less on weekdays than female children (P = 0.024). Female adolescents' mean body mass was below the normal and 60.0% showed menstrual irregularities; 4.9% of females bases were overweight and 2.4% obese. Male adolescents slept significantly less on weekdays than male children (P = 0.001); significant differences were shown for fat-free mass (P = 0.014); however, 3.7% were overweight. All daily energy and macronutrient intakes were significantly different according to age and gender, with exception for fibre and energy intake in females (P = 0.057 and P = 0.052, respectively), and for protein in males (P = 0.068). Female and male adolescents demonstrated significant lower energy availability (32.8 ± 9.4 kcal/kg FFM/day and 45.1 ± 14.7 kcal/kg FFM/day) than children (45.8 ± 8.7 kcal/kg FFM/day and 53.8 ± 9.1 kcal/kg FFM/day), respectively. Significant low intakes of important vitamins and minerals were reported. Most of the participants did not eat or drink during or immediately after training sessions.

CONCLUSION

Acrobatic gymnasts revealed low BF, short sleep duration and macro- and micronutrients inadequate intakes. The Female Athlete Triad was demonstrated by female adolescent gymnasts. What is Known: • Adequate dietary intake is an important resource for athletes' short and long-term health and performance. • There are no published studies in acrobatic gymnasts' sleep, body composition or dietary intake. What is New: • This study provides the first data on significant differences in energy intake and availability between acrobatic gymnasts; overweight and obesity were present in females. • Macro and micronutrients were inappropriate. Female Athlete Triad was observed in female adolescent acrobatic gymnasts.

Integrated Framework of Load Monitoring by a Combination of Smartphone Applications, Wearables and Point-of-Care Testing Provides Feedback that Allows Individual Responsive Adjustments to Activities of Daily Living

Athletes schedule their training and recovery in periods, often utilizing a pre-defined strategy. To avoid underperformance and/or compromised health, the external load during training should take into account the individual's physiological and perceptual responses. No single variable provides an adequate basis for planning, but continuous monitoring of a combination of several indicators of internal and external load during training, recovery and off-training as well may allow individual responsive adjustments of a training program in an effective manner. From a practical perspective, including that of coaches, monitoring of potential changes in health and performance should ideally be valid, reliable and sensitive, as well as time-efficient, easily applicable, non-fatiguing and as non-invasive as possible. Accordingly, smartphone applications, wearable sensors and point-of-care testing appear to offer a suitable monitoring framework allowing responsive adjustments to exercise prescription. Here, we outline 24-h monitoring of selected parameters by these technologies that (i) allows responsive adjustments of exercise programs, (ii) enhances performance and/or (iii) reduces the risk for overuse, injury and/or illness.

How well does a commercially available wearable device measure sleep in young athletes?

The validity of a commercially available wearable device for measuring total sleep time was examined in a sample of well-trained young athletes during night-time sleep periods and daytime naps. Participants wore a FitBit HR Charge on their non-dominant wrist and had electrodes attached to their face and scalp to enable polysomnographic recordings of sleep in the laboratory. The FitBit automatically detected 24/30 night-time sleep periods but only 6/20 daytime naps. Compared with polysomnography, the FitBit overestimated total sleep time by an average of 52 ± 152 min for night-time sleep periods, and by 4 ± 8 min for daytime naps. It is important for athletes and practitioners to be aware of the limitations of wearable devices that automatically detect sleep duration.

The Effects of Sleep Extension on Sleep, Performance, Immunity and Physical Stress in Rugby Players

(1) Background: The purpose of the present study was to examine the efficacy of sleep extension in professional rugby players. The aims were to: (i) characterise sleep quantity in elite rugby players and determine changes in immune function and stress hormone secretion during a pre-season training programme; (ii) evaluate the efficacy of a sleep extension intervention in improving sleep, markers of physical stress, immune function and performance. (2) Methods: Twenty five highly trained athletes from a professional rugby team (age (mean ± SD) 25 ± 2.7 years; height 1.87 ± 0.07 m; weight 105 ± 12.1 kg) participated in a six week pre-post control-trial intervention study. Variables of sleep, immune function, sympathetic nervous activity, physiological stress and reaction times were measured. (3) Results: Sleep extension resulted in a moderate improvement in sleep quality scores ([mean; ± 90% confidence limits] −24.8%; ± 54.1%) and small to moderate increases in total sleep time (6.3%; ± 6.3%) and time in bed (7.3%; ± 3.6%). In addition, a small decrease in cortisol (−18.7%; ± 26.4%) and mean reaction times (−4.3%; ± 3.1%) was observed following the intervention, compared to the control. (4) Conclusions: Professional rugby players are at risk of poor sleep during pre-season training, with concomitant rises in physical stress. Implementing a sleep extension programme among professional athletes is recommended to improve sleep, with beneficial changes in stress hormone expression and reaction time performance.

Sleep habits and strategies of ultramarathon runners

Among factors impacting performance during an ultramarathon, sleep is an underappreciated factor that has received little attention. The aims of this study were to characterize habitual sleep behaviors in ultramarathon runners and to examine strategies they use to manage sleep before and during ultramarathons. Responses from 636 participants to a questionnaire were considered. This population was found to sleep more on weekends and holidays (7–8 h to 8–9 h) than during weekdays (6–7 h to 7–8 h; p < 0.001). Work was a mediator of napping habits since 19–25% reported napping on work days and 37–56% on non-work days. There were 24.5% of the participants reporting sleep disorders, with more women (38.9%) reporting sleep problems than men (22.0%; p < 0.005). Mean (±SD) sleepiness score on the Epworth Sleepiness Scale was 8.9 ± 4.3 with 37.6% of respondents scoring higher than 10, reflecting excessive daytime sleepiness. Most of the study participants (73.9%) had a strategy to manage sleep preceding an ultramarathon, with 54.7% trying to increase their opportunities for sleep. Only 21% of participants reported that they had a strategy to manage sleep during ultramarathons, with micronaps being the most common strategy specified. Sub-analyses from 221 responses indicated that sleep duration during an ultramarathon was correlated with finish time for races lasting 36–60 h (r = 0.48; p < 0.01) or > 60 h (r = 0.44; p < 0.001). We conclude that sleep duration among ultramarathon runners was comparable to the general population and other athletic populations, yet they reported a lower prevalence of sleep disorders. Daytime sleepiness was among the lowest rates encountered in athletic populations, which may be related to the high percentage of nappers in our population. Sleep extension, by increasing sleep time at night and daytime napping, was the main sleep strategy to prepare for ultramarathons.

The Effects of the Removal of Electronic Devices for 48 Hours on Sleep in Elite Judo Athletes

This study examined the effects of evening use of electronic devices (i.e., smartphones, etc.) on sleep quality and next-day athletic and cognitive performance in elite judo athletes. Over 6 consecutive days and nights, 23 elite Australian judo athletes were monitored while attending a camp at the Australian Institute of Sport (AIS). In 14 athletes, all electronic devices were removed on days 3 and 4 (i.e., for 48 hours: the "device-restricted group"), whereas 9 were permitted to use their devices throughout the camp (the "control group"). All athletes wore an activity monitor (Readiband) continuously to provide measures of sleep quantity and quality. Other self-reported (diary) measures included time in bed, electronic device use, and rate of perceived exertion during training periods. Cognitive performance (Cogstate) and physical performance (single leg triple hop test) were also measured. When considering night 2 as a "baseline" for each group, removal of electronic devices on nights 3 and 4 (device-restricted group) resulted in no significant differences in any sleep-related measure between the groups. When comparing actigraphy-based measures of sleep to subjective measures, all athletes significantly overestimated sleep duration by 58 ± 85 minutes (p = 0.001) per night and underestimated time of sleep onset by 37 ± 72 minutes (p = 0.001) per night. No differences in physical or cognitive function were observed between the groups.

CONCLUSION

This study has shown that the removal of electronic devices for a period of two nights (48 hours) during a judo camp does not affect sleep quality or quantity or influence athletic or cognitive performance.

Sleep and Athletic Performance

Sleep is an essential component of health and well-being, with significant impacts on physical development, emotional regulation, cognitive performance, and quality of life. Along with being an integral part of the recovery and adaptive process between bouts of exercise, accumulating evidence suggests that increased sleep duration and improved sleep quality in athletes are associated with improved performance and competitive success. In addition, better sleep may reduce the risk of both injury and illness in athletes, not only optimizing health but also potentially enhancing performance through increased participation in training. Despite this, most studies have found that athletes fail to obtain the recommended amount of sleep, threatening both performance and health. Athletes face a number of obstacles that can reduce the likelihood of obtaining proper sleep, such as training and competition schedules, travel, stress, academic demands, and overtraining. In addition, athletes have been found to demonstrate poor self-assessment of their sleep duration and quality. In light of this, athletes may require more careful monitoring and intervention to identify individuals at risk and promote proper sleep to improve both performance and overall health. This review attempts to highlight the recent literature regarding sleep issues in athletes, the effects of sleep on athletic performance, and interventions to enhance proper sleep in athletes.

A Subjective Assessment of the Prevalence and Factors Associated with Poor Sleep Quality Amongst Elite Japanese Athletes

Background

The amount, quality, and timing of sleep are considered important for athletes’ ability to train, maximize training responses, and recover. However, some research has shown that elite athletes do not obtain sufficient sleep. Based on this background, researchers recently started to assess and manage sleep in elite athletes.

The purpose of this study was to clarify the prevalence of poor sleep quality and its associated factors amongst elite Japanese athletes.

Methods

Eight hundred and ninety-one candidates for the 17th Asian Games Incheon 2014, who were over 20 years old, participated in this study. They completed a questionnaire that included the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale, two-question case-finding instruments, and a checklist for sleep hygiene. Data from 817 of the 891 athletes (91.7%) with no missing values were analyzed.

Results

The mean time in bed was 7 h and 29 min. Two hundred and twenty-nine (28.0%) athletes showed a PSQI global score above the clinical criteria. A multiple logistic analysis revealed that sleep quality was significantly associated with five factors: “time in bed,” “eating breakfast every morning,” “avoiding the use of electronic devices (PC, smartphone, etc.) just before bedtime,” “depressive mood”, and “not thinking about troubles while in bed.” Forty percent of athletes reported they had been informed by someone about “snoring loudly” and/or “leg twitching or jerking during sleep.”

Conclusions

The results of this study demonstrate that 28% of the athletes showed the PSQI score above the cutoff for poor sleep quality (> 5.5), which suggests that there may be a high prevalence of poor sleep quality in this population of athletes. To improve athletes’ sleep, the five factors associated with sleep quality should be emphasized in athletes’ sleep education. Furthermore, in medical evaluations of athletes, it may be desirable to include screening for sleep disorders.

No Compromise of Competition Sleep Compared With Habitual Sleep in Elite Australian Footballers

Purpose: To assess the impact of match-start time and days relative to match compared with the habitual sleep characteristics of elite Australian Football (AF) players. Methods: 45 elite male AF players were assessed during the preseason (habitual) and across 4 home matches during the season. Players wore an activity monitor the night before (−1), night of (0), 1 night after (+1), and 2 nights (+2) after each match and completed a self-reported rating of sleep quality. A 2-way ANOVA with Tukey post hoc was used to determine differences in sleep characteristics between match-start times and days relative to the match. Two-way nested ANOVA was conducted to examine differences between competition and habitual phases. Effect size ± 90% confidence interval (ES ± 90% CI) was calculated to quantify the magnitude of pairwise differences. Results: Differences observed in sleep-onset latency (ES = 0.11 ± 0.16), sleep rating (ES = 0.08 ± 0.14), and sleep duration (ES = 0.08 ± 0.01) between competition and habitual periods were trivial. Sleep efficiency was almost certainly higher during competition than habitual, but this was not reflected in the subjective rating of sleep quality. Conclusions: Elite AF competition does not cause substantial disruption to sleep characteristics compared with habitual sleep. While match-start time has some impact on sleep variables, it appears that the match itself is more of a disruption than the start time. Subjective ratings of sleep from well-being questionnaires appear limited in their ability to accurately provide an indication of sleep quality.

Descriptive Values for Dancers on Baseline Concussion Tools

CONTEXT

  Capturing baseline data before a concussion can be a valuable tool in individualized care. However, not all athletes, including dancers, have access to baseline testing. When baseline examinations were not performed, clinicians consult normative values. Dancers are unique athletes; therefore, describing values specific to dancers may assist those working with these athletes in making more informed decisions.

OBJECTIVE

  To describe values for key concussion measures of dancers. Our secondary aim was to examine whether differences existed between sexes and professional status. Finally, we explored factors that may affect dancers' scores.

DESIGN

  Cross-sectional study.

SETTING

  Professional dance companies and a collegiate dance conservatory.

PATIENTS OR OTHER PARTICIPANTS

  A total of 238 dancers (university = 153, professional = 85; women = 171; men = 67; age = 21.1 ± 4.8 years).

MAIN OUTCOME MEASURE(S)

  We calculated the total symptom severity from the Sport Concussion Assessment Tool-3rd edition; the Standardized Assessment of Concussion score; the modified Balance Error Scoring System score; and the King-Devick score for each participant. Group differences were analyzed with Mann-Whitney or t tests, depending on the data distribution. We used bivariate correlations to explore the effects of other potential influencing factors.

RESULTS

  Participants demonstrated the following baseline outcomes: symptom severity = 16.6 ± 12.8; Standardized Assessment of Concussion = 27.5 ± 1.8; modified Balance Error Scoring System = 3.2 ± 3.1 errors; and King-Devick = 41.5 ± 8.2 seconds. A Mann-Whitney test revealed differences in King-Devick scores between female (40.8 ± 8.0 seconds) and male (43.4 ± 8.4 seconds) dancers ( P = .04). An independent-samples t test also demonstrated a difference in modified Balance Error Scoring System scores between female (2.95 ± 3.1 errors) and male (3.8 ± 3.1 errors) dancers ( P = .02). Age, hours of sleep, height, and history of concussion, depression, or injury did not display moderate or strong associations with any of the outcome measures.

CONCLUSIONS

  Dancers' symptom severity scores appeared to be higher than the values reported for other athletes. Additional studies are needed to establish normative values and develop a model for predicting baseline scores.

Impact of short- compared to long-haul international travel on the sleep and wellbeing of national wheelchair basketball athletes

Currently, very little is known about the impact of short- or long-haul air travel on the sleep and wellbeing of wheelchair basketball athletes. Eleven national wheelchair basketball athletes wore actigraphy monitors prior, during, and after air travel to the United Kingdom. Upon arrival, participants rated their subjective jet-lag, fatigue, and vigor. Individuals traveled to the United Kingdom from different locations in Australia, the United States, and Europe and were categorised according to travel length [LONG (up to 30.2 h) or SHORT (up to 6.5 h)]. Linear mixed models determined effects of travel length on sleep and subjective ratings of jet-lag, fatigue, and vigor. During competition, subjective fatigue and jet-lag were substantially higher (ES = 0.73; ±0.77) and (ES = 0.57; ±0.60), subjective vigor was lower (ES = 1.94; ±0.72), and get-up time was earlier (ES = 0.57; ±0.60) for LONG when compared to SHORT. Travelling greater distances by airplane had a larger effect on subjective ratings of jet-lag, fatigue and vigor, rather than sleep. Irrespective of travel group, sleep and subjective responses were compromised, reflecting the travel requirements, competition-mediated influences, and/or due to a change in environment.

Cracking the code for maintaining quality training in Olympic distance triathlon: lessons learnt from a squad of elite Scandinavian athletes

Objective

High-quality training is a key determinant of performance in the Olympic distance triathlon and is potentially influenced by a unique array of context-specific biopsychosocial factors. Our objective was to explore and describe these factors among squad members of a university-based, elite Olympic distance triathlete developmental programme.

Method

A qualitative investigation using a visual communication tool-assisted focus group and longitudinal semistructured individual interviews was conducted. Responses were solicited from the University of Southern Denmark’s elite triathlon team (n=8), and inductive coding from the focus group formed the basis of questions for the two rounds of individual interviews 11 months apart. All interviews were transcribed verbatim and then analysed thematically.

Results

Seventeen context-relevant factors were identified and 10 themes emerged, these being ‘the cold weather ritual’, ‘digestive system conditioning’, ‘the curse of the night owl’, ‘the strings attached to sponsorship’, ‘my coach—my rock’, ‘mood maintenance’, ‘the asynchronous training rhythm’, ‘psychological slavery’, ‘the legacy of the asphalt tattoo’ and ‘the tension of family and friends’.

Conclusions

By reflecting on their personal training vortex, elite triathletes were able to provide context-relevant insights into the maintenance of training quality over the course of a competitive season. Further research is required to elucidate whether and how biopsycholosocial factors can be modified to optimise the achievement of training goals.